A low-latency method for hybrid edge buffering in 5G fronthaul network

Abstract

The invention discloses a 5G fronthaul network hybrid edge cache low-latency method, which first constructs a 5G fronthaul network edge cache network scene between a core server, a cell base station, and a user, and then extracts all information from a mobile user's request for network content. The name of the requested network content and the corresponding number of requests are maintained into an information matrix and clustered, and then the cache value of each network content in each cluster is calculated, and based on this, the base station and each mobile user store network content. The hybrid cache strategy, and the establishment of EMD-ARIMA prediction model and cache replacement strategy, and finally mobile users obtain the required network content, so as to reduce the cache redundancy between users, improve the utilization of network resources, and reduce the service delay of 5G fronthaul network And relieve the link pressure of the network.

Description

technical field [0001] The invention belongs to the technical field of wireless communication, and more specifically relates to a low-latency method for hybrid edge buffering in a 5G fronthaul network. Background technique [0002] In recent years, with the rapid development of the mobile Internet, the emergence of various emerging communication services and emerging technologies such as the Internet of Things, the development of 5G mobile communication networks has been promoted. In addition, the popularity of mobile smart terminals has led to continuous growth of mobile data traffic. According to industry estimates, there will be about 50 billion mobile terminal devices with network connection functions accessing the network in the world in 2020, and the capacity of the fifth-generation mobile communication system needs to be increased by 1000 times in the future. [0003] The massive connections of terminals and the surge in traffic have put enormous pressure on the exis...

AI Technical Summary

Problems solved by technology

However, this caching method does not take into account the specific composition categories of users in each community (such as staff or students, etc.), their needs for network content are different, and their requests for network content are not necessarily included in the most popular In network content, the caching strategy should comprehensively consider the specific requests of various types of users and cache on demand; in addition, each user has different request levels for different network content, that is, each user has different interests and hobbies

If the mobile user's request is not included in the analysis, but only the popularity of the network content is considered, then different devices will cache the same network content with a high probability, resulting in a large number of cache redundancy problems, making the cache space unusable. less than fully utilized

[0005] On the other hand, the popularity of network content is time-varying, that is, users' requests for network content will change over time, which also makes it difficult for traditional passive caching strategies to achieve better caching effects

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